What are MF and LF requests? LF, MF, HF - types of key queries, how they are deciphered and how to determine their frequency! High and low frequency queries

Useful tips

The search query is the query that the user enters into the search:

The frequency is largely explained by the topic and area of business, as well as region, seasonality and search engine.

You can check the frequency using Yandex.Wordstat.

Types of search queries by their frequency

How to select low-frequency queries? Take everything that Wordstat shows, up to 1 impression per month. The more low frequency at the start of work, the more traffic there will be.
How to promote low-frequency queries? These are the simplest and most undemanding requests; they do not need to be supported by links - you just need to create relevant content: write articles, news, product cards that will answer the user’s question as meaningfully and accurately as possible.
Traffic for such queries will begin to grow immediately, but perhaps slowly: the queries are low-competitive, the results may not be impressive at first, but the more such queries are implemented on the site, the higher its traffic will ultimately be.

Highly competitive low-frequency requests do occur, but rarely - mainly in narrow commercial niches with high competition. That is, there are very few people who enter such queries, bringing your site to the top will not be easy, but if a user comes to your site, then most likely he will become a buyer.

Mid-frequency queries, their concept and features

How many mid-frequency queries are there? Midrange is a little more popular than bass. Mid-frequency and low-frequency queries are the basis for website promotion, because there are the most of them. Using both groups of requests, you can achieve optimal traffic with not the largest investments.

It is more difficult to promote a site on a commercial medium than on an informational one, and this must be taken into account: commercial queries are selling ones, and the competition for them is higher. For mid-frequency queries, the number of offers corresponds to the level of demand: there are indeed quite a few sites that are promoted primarily by mid-frequency queries. For example, on the Internet more than one company offers “buy plastic windows inexpensively”, so be prepared that working on the site in this case can take quite a lot of time.

High-frequency queries, their concept and features

What queries are considered high-frequency? Those that users enter in search most often - more than 1000 times a month, for example:

High-frequency queries are a wide variety and total number of options: there are not only informational and commercial queries, but also branded queries that receive a lot of traffic. But such queries are extremely highly competitive, so the highest frequency queries are the most expensive in all respects.

Another disadvantage of high-frequency queries in Yandex and Google is not the highest conversion: it is not clear what the user wants when entering a query into the search bar "laptop screen". Does he need care information, addresses of workshops where it can be repaired or replaced, or some technical specifications? And the contents of the page may not be what he is looking for at all.

How to determine whether a high-frequency query is high or not? Use the same Yandex.Wordstat.
How to promote high-frequency queries? Long and expensive. To get to the top of the search results, you will have to work long and hard on the site, investing impressively, including financially. It must be taken into account that especially the highest-frequency queries (Yandex or Google - it doesn’t matter) mean a huge flow of audience, including non-targeted ones, and extremely high competition.

What queries are best to choose for promotion?

What queries – low-frequency, medium- or high-frequency – should you collect for search engine optimization of your Internet site? The ideal queries for promotion are low-frequency and highly competitive, but this is rarely a dream come true for the optimizer and the client. Therefore, which queries are best to choose for your site depends on the site itself.

If SEO has not been carried out before, the site is not optimized and you are just at the beginning of the journey, then you need to first take on the low frequencies and work on them, gradually connecting the midrange and high frequencies.

If the site is maximally optimized for midrange and low frequency, take on high frequency.

You can also select queries for promotion based on the optimization vector:

if the site is developing for demand in a direction or area as a whole, use HF;
if you need to attract targeted visitors who are looking for one or more areas of your company’s work, use more SP;
if you need high conversion and sales growth, focus on low frequencies.

Many novice optimizers ask questions regarding query frequencies. What are LF, MF and HF?? How do you determine if a query is high-frequency or low-frequency? Does the theme of the site affect the assignment of a request to one of the intervals? And so on. We will try to answer all these questions, as well as reveal in more detail some points regarding frequencies.

Definitions

Please note that you should not confuse the terms “ frequency" And " frequency“! Frequency is a characteristic of a periodic process, measured in the number of units over a certain period of time. Frequency is a characteristic of the occurrence of a given object (word) among a certain set and is measured as a percentage. Roughly speaking, for our case, request frequency is how many times a month a given key phrase was searched in a search engine, and request frequency(let's say on a page) is the percentage of the query content (word) on the page in question. This article will only discuss the concept of search frequency for a specific key phrase.

HF (high frequency) queries – the most requested word (words, phrases) in your topic (most popular queries).
LF (low frequency) queries - words and phrases that are requested with low frequency in search engines and relate to your topic.
midrange (mid-frequency) request - something in between LF and HF (later there will be an exact quantitative definition).

Competitive request– this is a query for which it is difficult to get to the top of the sickle (the first results in a search engine) due to the competition of sites relevant to this query.
Highly competitive request– a query in which there are a lot of competitors for a given key phrase in the sickle.
Low competitive request– a request in which internal optimization factors are sufficient for the site to be on the first page of the sickle for a given key phrase (word).

Significance of the request– the concept is subjective and is determined by the webmaster (optimizer, site owner) independently, depending on the topic and goals of the site (for more details on significance, see here What is the minimum significant request sampling frequency). The frequency below which queries are not included in the significant sample and are not reviewed for analysis is called minimum significant sampling rate.

How to determine RF requests for your site

To determine the frequency of search queries in search engines, there are services that provide this information. For example, to search for frequencies of Russian-language words, you can use the service provided by the Yandex PS - query statistics. To search for statistics on English words, you can use the KeywordDiscovery service.

Let's say that you have a website for the production of air ducts (for those who are not familiar with the concept of air ducts, you can read here: about air ducts). We enter the phrase “air duct” into wordstat and get a list of relevant queries, where “air duct” is in first place with 16,949 impressions per month. But in the right column we can also see the word “fans”, which is searched much more often (75485 per month), however, fans may not relate to your topic and, therefore, considering the word “fan” in your topic as a high-frequency query will be incorrect. That is, from the entire set of queries, you need to select the most significant ones (down to words with a minimum significant frequency, which is determined by the webmaster or optimizer). And this sample can be divided into HF and LF. Sampling meaningful queries is the definition semantic core(this is what optimizers mean when they say that “the theme of the site affects whether a request is considered HF, MF or LF”).

Precise determination of the boundaries between HF, MF and LF

So you have a sample. Now we need to remember probability theory and the distribution function. Let us note once again, although this is intuitively clear, that midrange- This average frequency between HF and LF. However, it can be difficult to determine this average. For example, HF “air duct“ – 16949 and LF “sale production of air ducts“ – 6 requests/month. What will be the midrange then?

If we take the arithmetic average, then it turns out that among the sample we have no midrange at all. To do this, consider the sample dependence on the graph (Figure 1.1). It is clear from the graph that the dependence is logarithmic, since if the abscissa axis (request number) and ordinate axis (request frequency) are taken on a logarithmic scale, then with some error we will obtain a linear histogram of request frequencies. This means that the SP will be in the middle of this linear regression.

Figure 1.1 – Graph of the distribution of search queries by frequency (the axes are taken on a logarithmic scale).

Let us introduce the notation
hvc— maximum value of RF request frequency;
Hnch— minimum frequency value (minimum significant frequency) of the request

Then, it can be argued that

Hch = /(Hch – Hnch)

(square root of the difference between the maximum and minimum frequencies)

The above dependence comes from the property of the logarithm log(x)/2 = log(x^0.5) = log(/x).

Often Hnch much less hvc and, therefore, it can be neglected, we get:

Hc = /Hc

Now let’s check these values using the example “ air ducts“:

Chnch = 16949, Chnch = 6

Hch = /(16949-6) = /16943 ≈ 130

A value of 130 will be mid-frequency meaning. Now it is necessary to determine the interval in which the frequency will be considered average. To do this, divide the linear interval into 3 equal parts, so each part will have its own frequency range. The deviation from the absolute average frequency will be approximately equal to 33% .

Midrange Width:

D = log(Xwh)/3 = 3 /log(Xwh) = 1.41;

This means the interval from 10 log(Hc) – D/2 before 10 log(Hc) + D/2 will be considered the mid-frequency interval. In our case it is

This interval includes such keywords as (information as of March 6, 2008 00:00 Moscow time): air duct cleaning, air ducts price, PVC air ducts, price air ducts, etc. Everything that is above the 646 mark will be high frequency, and below 26 will be low frequency. All queries whose search frequency is in the range from 26 to 646 are entitled to be called mid-frequency queries.

Conclusion

The basic relationships for determining the mid-frequency interval are as follows:

Xsch.min = 10 log(Hc) – D/2, Xcount.max = 10 log(Hc) + D/2
Hc = /Hc, D = log(HWH)/3

Note that when determining the SP interval, you should take into account the individual sample for your site and it may not always have a logarithmic dependence. However, the above formulas are suitable for most keyword cases (tested on several dozen topics). For another characteristic of the behavior of the search frequency of key phrases, it is necessary to look for a function that describes the distribution of frequencies.

LF, MF, HF- these abbreviations that mean low frequency, mid-frequency And high frequency requests accordingly. That is, how many times the query was asked in search engines per month.

The lower the frequency of requests for some key phrases, the easier it is, as a rule, to promote the site. But this is not always the case, since a lot still depends on the competition of the request.

It is difficult to name the exact gradation of how many requests a high-frequency driver, mid-frequency driver and low-frequency driver should have per month. It all depends on the topic. Approximate numbers are as follows:

LF - less than 150 requests per month
MF - from 150 to 5000 requests per month
HF - from 5000 requests per month

These numbers are approximate and, as already mentioned, everything depends on the topic. Those. in some topics, it is possible that 500 requests per month will be considered low.

How to check the frequency of requests in Yandex

You can check the request frequency in Yandex at wordstat.yandex.ru (free). However, you should not trust 100% of the data that is shown there, since these are statistics of Yandex Direct requests. These values can be used mainly for rough calculations. For example, if request 1 was requested 100 times, and request 2 200 times, then we can safely say that the frequency for the search will differ by approximately two times.

I advise you to check the request frequency in the following format:

The rule is very simple: write your query in quotes and put an exclamation point “!” before each keyword. This way you can determine the frequency of exactly the phrase you are looking for (with exact endings). However, even the information you received will be based on data from the direct message. But this method will help track relative competition.

You can read more about the syntax in Wordstat in the articles

Keywords that are included in the semantic core of any project have, from which the priority of their promotion or use in their materials may change. One of these characteristics is the frequency of the request.

What is search frequency?

Query frequency is the number of times a user entered a given query into a search engine over a certain period of time. One of the most popular and accessible services for checking the frequency of search queries is the Yandex service - Yandex.Wordstat (wordstat.yandex.ru). Accordingly, the more frequent queries we use in our materials and articles, the more traffic we will receive. However, not everything is so simple and first you need to understand the types of frequency queries and their application.

Types of request frequencies

In SEO, it is customary to classify queries by their frequency. It is believed that the higher the request frequency, the more traffic it will bring(if you look purely at the numbers).

The frequency types are as follows:

High frequency requests, also known as HF requests.

Mid-frequency requests, also known as mid-range requests.

Low-frequency queries, also known as low-frequency queries.

This classification is used by SEO specialists in their work. For example, when communicating with colleagues, in order to identify traffic potential and difficulty in promoting a particular group of requests.

Request frequency as a relative value

Frequency is not an absolute value. She reflects user demand for certain goods or services in a specific niche. It turns out that if you take all the queries in the topic “laptops” and sort them by frequency, then the first place will be a single-word query with a frequency of 5,295,645 impressions per month (relatively speaking). If we are talking about the “cat food” niche, then the upper threshold there can be much lower, about 249,968 impressions per month.

It follows from this that we will assign a type to a request based on the upper threshold of frequency in the topic. As a result, we will have 3 groups, for each of which a frequency threshold will be assigned for phrases that are included in this group.

For example, for the topic “children’s trampoline” the boundaries will be as follows:

HF - everything above 20,000 impressions per month
MF - from 3,000 impressions per month
LF - up to 3,000 impressions per month

You shouldn’t get too attached to boundaries and spend a lot of time classifying requests by type, because... This segmentation is rather arbitrary and has no practical value.

High Frequency Queries (HF)

High-frequency queries (HF) are queries that have the highest frequencies among all queries in our chosen niche. As mentioned above, a high-frequency request can be either with a frequency of 5,295,645 impressions or with a frequency of 27,811 impressions, as can be seen from the example below. In some topics, for example, a request less than 5,000 is no longer high-frequency.

Almost alwayshigh-frequency queries are marker queries, single-word queries, or so-called.

An example of such queries could be “computer”, “car”, “apartment” and other general queries.

Photo 1: An example of a super-HF request for a niche with stable, heated demand.
Photo 2: According to statistics, cars are the second most popular topic of discussion among men.

An example of narrower, but high-frequency queries could be the following phrase (only if our niche is express weight loss courses):

Photo 3: Losing weight, losing excess weight is perhaps the most pressing problem for women. The frequency of the request indicates that there is a clear demand for this topic.

The request is not one-word, but the semantic meaning or intention of the user is clear from it, unlike the request “car”, when it is unknown whether to show him a site for car repair, washing or sale.

The advantage of high-frequency queries is the potential for large traffic. The difficulty is that there is unrealistic competition in high-frequency queries and getting to the top for them takes a lot of time and effort.

Important! Do not try to promote a young resource exclusively for HF requests; it will be much more profitable to focus on promoting mid-range and low-frequency requests for rapid growth of the project.

As practice shows, high-frequency queries make up no more than 5% of the semantic core of the project. There are cases when one general (HF) request covers 50% of the frequency of all other phrases from the kernel. This is a normal situation.

We can understand the relative difficulty in promoting a particular keyword by assessing its competition index. You can create the index yourself by analyzing the results, or you can use the Mutagen service, which will calculate the index using its own formula. For example, if we see that according to Mutagen the competition for a phrase is 25, then we will not move forward on it soon and it is better to focus on other, less competitive phrases.

Mid-frequency queries (MF)

Mid-frequency requests (MF) are a group of requests that follow HF requests. For different topics, mid-range requests can start from either 1,000 or 50,000 impressions per month.

Mid-frequency queries are usually (but not always!) less competitive than high-frequency queries. In them it is possible to find queries with a longer “tail” and less competition. In addition, the MF query in most cases contains more words. This way, it’s easier for us to understand the intention of the user who entered this request and show him an article with a solution to his problem or offer him a product.

Photo 4: Such queries make up about 10% of the semantic core of the project.

It is easier to promote mid-range requests than high-frequency ones (for the most part) and it can take less effort and time. However, in this case, it will also be important to look at the competitiveness of requests in order to build the right strategy for promoting documents (pages) on the site.

Low frequency queries (LF)

Low-frequency queries are queries whose frequency is less than 1000 or 100. It is this type of queries that is most interesting to SEO specialists and semanticists, because they can make up 80-90% of the entire semantic core.

Why are there more such requests? It's simple. Many people, when they enter a search query into a line, for example, Yandex, know in advance what they need.

Interesting fact! People learn to work with search. According to a study conducted by Yandex, in 2016 people entered 30% more 7-word phrases than in 2015. Thus, the “tail” of requests will continue to grow, and the user will refine his request more and more.

Example. There are 2 people - Petya and Masha, both want to buy a multicooker. Petya is an amateur in this matter and doesn’t know what types of multicookers there are, so he wants to look at all the possible options. Therefore, his request may look like a high-frequency one - “multi-cookers”.

Photo 5: As a first step, Petya decides to just see what he has to deal with.

Masha consulted with her friends and knows what product to buy. Therefore, her request may look like this: “multi-cooker polaris pmc 0347ad”.

Photo 6: Masha found out everything from her friends a long time ago and immediately went to compare prices.

Moreover, in this case, there may be several options for writing a request - “polaris multicooker”, “polaris pmc multicooker”, “buy polaris multicooker” and so on. If we assume that every person tries to find the multicooker model they are interested in, then there will be at least 100 requests.

In some topics, queries may appear due to a lack of knowledge or names of any things, diseases, or products. Differences in knowledge, vocabulary, and experience of people who enter queries into the search bar generate a large number of low frequency queries.

For example, one user types in the query: “How to grow a money tree?”, and the second user, who has more knowledge, writes “How to grow a crassula?”. Essentially, these requests are about the same thing, but the second request will have lower competition and frequency than the first.

Competition for low-frequency queries is usually small and moving up to 95% of them is not difficult.

Under no circumstances should low-frequency requests be ignored. There are often cases when a large number of low-frequency requests make up 80% of the project’s traffic due to quantity, while HF and MF requests are the remaining 20%.

Another characteristic feature of low frequency queries is the “long tail” of a query - that is, a query consisting of a large number of words. For example:

Photo 7: And also + free + no registration + no SMS.

Having assembled groups of similar low-frequency queries led by the 1st marker

Photo 8: Tails “do-it-yourself” and “at home” - these are twin brothers. Usually, if you see one in a request, sooner or later you will find the second one :).

We will receive a full-fledged group of requests and will be able to write good material that will advance among low-frequency requests and gradually, increasing the credibility of the project and document, will rise to the TOP also among high-frequency requests.

Results

We looked at the main types of HF, MF and LF requests. To summarize the main part, the following recommendations can be highlighted:

You should not focus on HF requests. If our core consists primarily of high-frequency queries, then difficulties will arise with its implementation and promotion. It is better to supplement it with midrange and bass and then implement it. In this case, it will be much easier to promote the project.

If we want to advance in HF requests, it is better to first assess the competition of each of them in order to better understand where the result will be faster.

Don't ignore low frequency requests. It is they, due to the quantity and total frequency, that help to cover all the semantics and desires of users and, as a result, receive traffic to the site.

Before introducing a nuclear system, it should be analyzed for the number of high frequencies, mid frequencies and low frequencies - this will help determine how complete the core is in front of us. If HF requests are 50%, midrange - 30%, and low frequency - 20%, then there is a potential for expansion of the frequency spectrum at the expense of midrange and low frequency. .

Greetings to the readers of my blog site! I'll start right away with a question. Do you already have a personal website or blog? Are you promoting it, if yes, then how? Have you heard of such concepts as: LF HF HF requests? Some of you may be surprised by these strange combinations of a couple of letters, but experienced bloggers are probably familiar with them and have already brought tangible benefits when promoting their blog. I’ll tell you in more detail what the decoding and meaning of these abbreviations are. Interesting? Read on.

When you start to promote your resource, everything matters. Site navigation, design, semantic load, and so on. But I would say that these points are secondary. What matters most is the content, that is, the articles that will be published. I’m sure many of you already know that using other sources is not only unethical towards other authors, but will also have a negative impact on the development of the blog. Texts must be unique, and for their successful promotion, keywords should be introduced into sentences.

Decoding

Before sharing with you information about the meaning of the terms mentioned and their usefulness in, let's get acquainted with the interpretation of queries:

HF – high-frequency ones, characterizing the industry, which are asked in searches more than 10,000 times, for example, “wooden doors”; such requests are general and do not carry any specifics;
midrange – mid-frequency, more specific than the previous one, usually consists of two or three words with a monthly search frequency of one thousand to ten thousand, for example – “ wooden interior door»;
LF – low-frequency, usually consisting of three or more words with a frequency of up to a thousand requests per month, for example - “ buy larch interior door at a profit».

I assume you all know the definition of the word “request,” but I’ll explain anyway. This is a word or phrase that fits into the search string. It turns out that LF, MF and HF are the query keys in SEO.

So, we understand that each article must be optimized for certain search queries. Keep in mind that website promotion using high-frequency phrases is more expensive, but worth it.

It is very important to implement keywords correctly so that users find answers to their questions when they land on your informative source. Otherwise, search engines will notice that guests of the resource do not stay on the site for long, and this will lead to a decrease in your ranking in the top results.

Do not try to include several many queries in one article, limit yourself to one or three.

The differences between keywords with different frequencies are as follows:

The lower the frequency, the fewer competitors and the greater the likelihood that your article will appear first or one of the first in search results.

I definitely recommend writing articles at the initial stage of site development, for low-frequency queries. Website sections are formed based on mid-frequency queries, and high-frequency ones for the index page of the website, that is, the main one.

We will define keywords for you

If you haven’t yet started analyzing your resource and selecting keywords for it, now is the time to start. After all, the sooner you learn to write articles correctly, the better for you and the promotion of your Internet project. A unique service from Yandex will come to our aid - Wordstat, which is a guide to the world of optimization and allows you to choose words for competent SEO. Once you enter this system, you will see a window like this.

If you do not have or have not yet registered your resource in this system, hurry up to do so, but you can start selecting words without registration. I entered the phrase " wooden doors ", set the region " Russia" and pressed the button " Pick up" Look what happened:

As you can see, this phrase is quite popular and in demand. But please note that the indicated number of queries located opposite the phrase indicates the total number of phrases found where yours appears, in this case "wooden doors" , For example, "wooden entrance doors" , "buy wooden doors" etc.

To view the number of phrases and their inflections only for a written phrase, you need to put it in quotes:

The situation has changed a little. The number 1463 is real, that is, the mentioned request is mid-frequency. If, for example, you sell plush hares in a specific city (Ekaterinburg) and provide for delivery and sale only within that city, then it makes sense for you to indicate a more specific region, up to your city. With the same success, you can look at the statistics of how many people per month are interested in plush hares in Yekaterinburg.

Be sure to use quotation marks, as I showed above, they will help you cut off unnecessary words in queries. There are several other useful techniques when working with this system. For example, you might want to match queries about doors, but not include responses like " wooden" Then in the search bar you need to specify the following combination of words and characters:

That is, before a word that you don't need, indicate a minus sign . When indicate a plus , then you assume that the keywords will be diluted with conjunctions and prepositions:

Exclamation mark helps to find all variants of queries in which your key is displayed (exact occurrence):

If, for example, you make not only doors, but also windows and balconies, then you can group your request in parentheses or separate words with a vertical line:

It is better for beginners to focus their attention on promoting low-frequency and mid-frequency queries, since high-frequency ones have great competition and promotion on them requires large financial investments (to buy links or advertising through Yandex Direct). Large companies that claim to conquer the market can afford such active promotion; it is difficult for one person to cope with this.

But don’t rush to get upset, this doesn’t mean that potential clients and subscribers will bypass you. Experience shows that promotion for low-frequency queries can attract a higher-quality audience. It turns out that it’s all about the ability to write high-quality articles for keywords.

You can fill your resource with low-frequency queries, confidently increase your readership and replenish your client base, and reaching the TOP is just around the corner!

I hope you have become familiar with the terms and made certain conclusions regarding exactly how you will promote your site in the near future. I would like to know about your real successes, share them in the comments to the articles, how you managed to achieve and over what period.

Starting to develop your blog is often difficult, but I guarantee you information support, so be sure to subscribe to the newsletter and invite your friends and colleagues!

See you later!

Best regards, Alexander Sergienko